A rotating and resonating turbine blade radiates an acoustic signal which, when detected by a stationary acoustic sensor, can be characterized by a Doppler waveform. The characteristics of the detected acoustic signal are well understood. However, the characteristic Doppler signal is masked by other sounds generated by turbine operation. The present invention provides an improved means of isolating the characteristic Doppler signal from those signal components that mask the Doppler signal in order to identify the causal blade and its vibration frequency.
In U.S. Pat. No. 4,422,333 a method and apparatus for detecting and identifying one or more excessively vibrating turbine blades is disclosed. At the heart of the invention is the use of a pressure microphone as an acoustic sensor embedded in the stationary casing of the turbine for listening to the sound radiated by a vibrating and rotating blade. Methods of processing the acoustic sensor output signal to separate the desired characteristic Doppler waveform from random noise and periodic background sounds that accompany it were introduced.
In U.S. Pat. Nos. 4,996,880 and 5,152,172 improved methods for separating the desired characteristic Doppler signal from the accompanying periodic background based upon physical characteristics of a resonant blade and the small speed perturbations exhibited by all turbines including those run at "constant speed" are disclosed. Improved Hilbert Transform detection methods for identifying the position of any resonating blade and the frequency at which it vibrates and means and methods to detect and locate blades vibrating at frequencies other than harmonics of the machine rotational speed such as is encountered in aeroelastic blade flutter were also introduced, along with improved detection methods incorporating pairs of acoustic sensors. Methods of introducing deliberate torsional vibration to a turbine-generator train were disclosed to analyze the resulting blade vibration as a means of characterizing the turbine blading. Lastly, means to detect aerodynamic events including condensation shock, rotating stall in an operating turbine, differential nozzle wear, and order-related torsional vibration were introduced.
The U.S. Pat. No. 4,422,333 presented satisfactory methodology for acquiring an information-bearing acoustic signal at a fixed site reflecting the dynamics of the rotating turbine blading. It further presented a satisfactory means of suppressing the random flow noise components that mask the periodic Doppler signal characteristic of a vibrating blade. However, it failed to provide an effective means of separating the periodic Doppler from other periodic tones present in the turbine.
The U.S. Pat. Nos. 4,996,880 and 5,152,172 describe the first principles for effective separation of the characteristic Doppler from masking periodic tones. A process deriving a "difference Doppler" signal was introduced. However, the implementation is flawed in that excessive measurement time is required, only a small portion of the measured data is actually used in the final computation, and multiple and different "answers" are possible due to a required selection of the actual data subset employed. Additionally, the process employs an unnecessary number of transformations between the time and frequency domains, resulting in a loss of precision and an increase in computational time. The display resolution is limited by the initial sample rate employed in data acquisition, and producing output results with "point-per-blade" resolution is technically infeasible. Finally, the method prescribes retaining an unnecessarily large body of measured data, increasing the amount of hardware storage required.